IEEE Transactions on Software Engineering
Maté: a tiny virtual machine for sensor networks
Proceedings of the 10th international conference on Architectural support for programming languages and operating systems
Dynamic plan migration for continuous queries over data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Contiki - A Lightweight and Flexible Operating System for Tiny Networked Sensors
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
A dynamic operating system for sensor nodes
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
VMSTAR: synthesizing scalable runtime environments for sensor networks
Proceedings of the 3rd international conference on Embedded networked sensor systems
Run-time dynamic linking for reprogramming wireless sensor networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Protothreads: simplifying event-driven programming of memory-constrained embedded systems
Proceedings of the 4th international conference on Embedded networked sensor systems
Asynchronous in-network prediction: Efficient aggregation in sensor networks
ACM Transactions on Sensor Networks (TOSN)
Query Processing in Sensor Networks
IEEE Pervasive Computing
Enabling large-scale storage in sensor networks with the Coffee file system
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Darjeeling, a feature-rich VM for the resource poor
Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems
Proceedings of the 7th International Workshop on Middleware Tools, Services and Run-Time Support for Sensor Networks
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Most sensor network applications are dominated by the acquisition of sensor values. Due to energy limitations and high energy costs of communication, in-network processing has been proposed as a means to reduce data transfers. As application demands may change over time and nodes run low on energy, get overloaded, or simply face debasing communication capabilities, runtime adaptation is required. In either case, it is useful to be able to migrate computations between neighboring nodes without losing runtime state that might be costly or even impossible to recompute. We propose stateful mobile modules as a basic infrastructure building block to improve adaptiveness and robustness of in-network processing applications. Stateful mobile modules are binary modules linked on the node itself. Even more importantly, they can be transparently migrated from one node to another, thereby keeping statically as well as dynamically allocated memory. This is achieved by an optimized binary format, a memory-efficient linking process and an advanced programming support.